code: def forward(self, inputs):
      if self.is_vd_mode:
          inputs = self._pool2d_avg(inputs)
      y = self._conv(inputs)
      y = self._batch_norm(y)
      return y
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import paddle
  from paddle import ParamAttr
  import paddle.nn
  import paddle.nn.functional
  from paddle.vision.ops import DeformConv2D
  from paddle.regularizer import L2Decay
  from paddle.nn.initializer import Normal, Constant, XavierUniform
label_desc: Use image node_id 2 for calling the ConvBNLayer obj's underlying member method code with example usage: obj.forward(inputs) and returns: y